Fuzzy Logic based Modelling and Simulation Approach for the estimation of Tire Forces

Jayachandran, Rajesh; Sharmila, A.; Narayanan, S.

doi:10.1016/j.proeng.2013.09.189

Cited by 13 publications

(10 citation statements)

References 10 publications

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“…It was found that the slip angle is directly related to the lateral force, which is usually defined as the force that the tire transmits to the road in the lateral direction, generating the required grip [ 8 , 9 ]. For this reason, a large and growing body of literature has also investigated their estimation [ 10 , 11 , 12 , 13 ]. Overall, these researches indicate that lateral and longitudinal tire-road forces depend on different parameters regarding the working conditions or the tire properties.…”

Section: Introductionmentioning

confidence: 99%

A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

Yunta

García-Pozuelo

Díaz

et al. 2018

Sensors

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Abstract:Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire's loss of grip and estimations of the lateral friction coefficient.

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Section: Introductionmentioning

confidence: 99%

A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

Yunta

García-Pozuelo

Díaz

et al. 2018

Sensors

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“…First, they used a sliding mode observer (angular velocity of the wheel was measured) to estimate the vehicle states, then using a recursive least square algorithm, they estimated the tire road friction coefficient. Jayachandran et al [119] developed a fuzzy logic based algorithm to estimate the value of longitudinal and lateral forces, also aligning moment based on slip ratio and slip angle. They used Magic Formula with known coefficients to calculate the tire forces and moment based on different slip values; then they defined a fuzzy membership function between the inputs (slip ratio, slip angle) and outputs (tire forces, aligning moment) of fuzzy-logic algorithm based on the calculated values.…”

Section: Pacejka Tire Modelmentioning

confidence: 99%

A technical survey on tire-road friction estimation

2017

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Lack of driver's knowledge about the abrupt changes in pavement's friction and poor performance of the vehicle's stability, traction, and ABS controllers on the low friction surfaces are the most important factors affecting car crashes. Due to its direct relation to vehicle stability, accurate estimation of tire-road friction is of interest to all vehicle and tire companies. Many studies have been conducted in this field and researchers have used different tools and have proposed different algorithms. This literature survey introduces different approaches, which have been widely used to estimate the friction or other related parameters, and covers the recent literature that contains these methodologies. The emphasize of this review paper is on the algorithms and studies, which are more popular and have been repeated several times. The focus has been divided into two main groups: experiment-based and model-based approaches. Each of these main groups has several sub-categories, which are explained in the next few sections. Several summary tables are provided in which the overall feature of each approach is reviewed that gives the reader the general picture of different algorithms, which are widely used in friction estimation studies.

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“…Data-based methods 35,37,38 can be seen as an intermediate step between stochastic and tyre model-based approaches. Stochastic approaches do not require any a priori information regarding the tyre–road interaction phenomena, but their dynamic response is limited (slow convergence) due to the steady-state behaviour ( x · = 0 ) assumed during the one-step prediction of the Kalman filter.…”

Section: Lateral Force Estimationmentioning

confidence: 99%

“…Finally, data-based methods have been introduced in Pasterkamp and Pacejka 35 and Luque et al 36 to model the tyre friction nonlinearities taking advantage of the fitting capabilities of Neural Networks (NN) 37 or fuzzy logic. 38 The accuracy of these methods depends strongly on the quality of the training datasets.…”

Section: Introductionmentioning

confidence: 99%

Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques

Acosta

Kanarachos

Blundell

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a comprehensive literature review on tyre force estimation and road grip recognition approaches. With the development of modern automotive control systems, a precise estimation of a large number of vehicle states is necessary to guarantee a robust actuation of the controller. Moreover, the estimation of these states must be carried out in a cost-effective and reliable way. The aim of this work is to provide a solid base for the development of automotive virtual sensors, and in particular, virtual tyre force sensors. An initial overview of the tyre force estimation problem is provided in the first section. Tyre and vehicle modelling, as well as observers for vehicle state estimation, are covered in detail in the second section. The third section introduces a brief discussion regarding the main limitations of direct tyre force measurement approaches. In the following sections, relevant works regarding three-axis tyre force estimation and road grip recognition are discussed. The review is structured around longitudinal force estimation, lateral force estimation, combined tyre force estimation, tyre self-alignment torque estimation and vertical tyre force estimation. Within each section, the most significant road grip identification approaches are introduced. An additional section, Road slope and bank angle compensation, describes relevant work on estimation methods for global chassis orientation. A brief summary of the presented approaches is provided in the section Summary of presented approaches. Finally, relevant conclusions and further research steps are given in the last section.

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Fuzzy Logic based Modelling and Simulation Approach for the estimation of Tire Forces

Cited by 13 publications

References 10 publications

A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

A technical survey on tire-road friction estimation

Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques

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